Sökning: "FPGA image processing"

Visar resultat 1 - 5 av 37 uppsatser innehållade orden FPGA image processing.

1. 1. Modeling, Simulation, and Injection of Camera Images/Video to Automotive Embedded ECU : Image Injection Solution for Hardware-in-the-Loop Testing

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

   Författare :Anton Lind; [2023]
   Nyckelord :ADAS; AD; ADS; HIL; Hardware in the loop; Hardware-in-the-loop; ECU; VCU; Automotive; Embedded; System; Systems; Camera; Image; Video; Injection; FPGA; MPSoC; Vivado; Vitis; VHDL; Volvo; Cars; FMC; HPC; LPC; MIPI CSI2; GMSL2; AMBA AXI4; Xilinx; RTL; Implementation; Synthesis; Intelectual Property; IP; Vehicle computing unit; Electronic control unit; TEB0911; TEF0007; TEF0010; CSI2 Tx; CSI2 Tx Subsystem; Zynq; SerDes; AXI4; AXI4-Lite; Programmable Logic; PL; Processor System; PS; C; C ; Video test pattern generator; VTPG; Axi traffic generator; ATG; Ultrascale ; Virtual input output; VIO; Integrated logic analyzer; ILA; Interface Unit;

   Sammanfattning : Testing, verification and validation of sensors, components and systems is vital in the early-stage development of new cars with computer-in-the-car architecture. This can be done with the help of the existing technique, hardware-in-the-loop (HIL) testing which, in the close loop testing case, consists of four main parts: Real-Time Simulation Platform, Sensor Simulation PC, Interface Unit (IU), and unit under test which is, for instance, a Vehicle Computing Unit (VCU). LÄS MER

3. 2. Low-power Acceleration of Convolutional Neural Networks using Near Memory Computing on a RISC-V SoC

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Kristoffer Westring; Linus Svensson; [2023]
   Nyckelord :FPGA; ASIC; Near Memory Computing; RISC-V; Convolutional Neural Network; Technology and Engineering;

   Sammanfattning : The recent peak in interest for artificial intelligence, partly fueled by language models such as ChatGPT, is pushing the demand for machine learning and data processing in everyday applications, such as self-driving cars, where low latency is crucial and typically achieved through edge computing. The vast amount of data processing required intensifies the existing performance bottleneck of the data movement. LÄS MER

4. 3. How does a fly avoid obstacles?

   Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap; Linköpings universitet/Tekniska fakulteten

   Författare :Stian Lockhart Pedersen; [2022]
   Nyckelord :Image processing; Time-To-Impact; TTI;

   Sammanfattning : An implementation of a Time-To-Impact(TTI) algorithm in a language more closely related to small compact devices, such as a Field-programmable gate array(FPGA), needs tobe developed. The algorithm is based on an article written by Åström and Forchheimer [1]. LÄS MER

5. 4. FPGA Implementation of the ORB Algorithm

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Xinyuan Zhang; Emil Sturk Sellstedt; [2022]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Image feature extraction has become a key technology in the field of autonomous Artificial Intelligence. The algorithm Oriented FAST and Rotated BRIEF (ORB), uses established technologies in image processing to allow a computer to ”see” and navigate its surroundings. LÄS MER

7. 5. Convolutional Neural Network FPGA-accelerator on Intel DE10-Standard FPGA

   Master-uppsats, Linköpings universitet/Elektroniska Kretsar och System

   Författare :Yue Tianxu; [2021]
   Nyckelord :Convolutional Neural Network; FPGA-accelerator;

   Sammanfattning : Convolutional neural networks (CNNs) have been extensively used in many aspects, such as face and speech recognition, image searching and classification, and automatic drive. Hence, CNN accelerators have become a trending research. Generally, Graphics processing units (GPUs) are widely applied in CNNaccelerators. LÄS MER